Online service providers generally provide content via the Internet to a browser on a computing device such as a personal computer used by a human user. Some online service providers, such as Facebook® and Myspace®, offer social networking sites that display several forms of user-generated events. For example, social networking sites typically display pictures, comments, notes, status updates, songs, videos, and more.
The content on social networking sites is typically generated by end-users that utilize the online service in order to share content and connect with others. Other online service providers, such as the news sites of CNN® and ESPN®, employ writers who generate the content that is distributed on the site. Still other online service providers, such as Yahoo!® and Google®, offer search services to direct users to content, some of which may be generated by other online service providers. For example, a user may use Yahoo!® search to search for “baseball scores.” The user may be provided with search results that include baseball scores provided by Yahoo!® Sports and/or baseball scores provided by ESPN®.
Content generated for a particular user may be called individualized content. For practical and economic reasons, the order and selection of individualized content may be automated. For example, search providers rank search results based on the frequency by which previous users clicked on the results when submitting a similar query. Social networking sites display events in the order that they occurred.
Some online service providers employ producers to manage the display of content on the site. However, human producers may be impractical for sites that provide individualized content for thousands or millions of users. Also, many human producers are biased towards a particular type of content, and the producers make selections either based on personal preferences or based on what they perceive to be the preferences of their most valued users.
Online service providers generally use computer-implemented techniques for automatically selecting either the latest content, or the content that is perceived to be the most relevant content based upon statistical norms. According to current techniques, users that differ from the statistical norm are commonly not presented with any desired content. Further, users are often bombarded with content that is associated with a few other users who most recently used the service. In some instances, the entire screen may be filled with content related to another user who recently uploaded a popular photo album or wrote a popular note.
Unless a user is seeking the most popular content, the current techniques for selecting content frequently leave users unsatisfied. Moreover, the current techniques often convey only a very limited amount of information on the screen to the user.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.